pyawx 0.1.1

Python client for managing AWX automation platform

🤖 PyAWX

Python client for managing AWX automation platform.

📌 Table of Contents

• ✨ Features
• 📚 Documentation
• 📦 Installation
• 📖 Usage
• 🤝 Contributing
• 🧪 Testing
• 🛠️ Roadmap

✨ Features

• Authentication support: Built-in support for Basic Auth and OAuth2.
• Data validation: Pydantic models ensure that payloads conform to the AWX API's expected structure.
• Extensibility: Easily extendable to support new AWX resources or custom workflows.

📚 Documentation

Each module is documented in detail and can be explored using pdoc. Below is an overview of the key modules:

• pyawx.auth: Authentication classes for Basic Auth and OAuth2.
• pyawx.http: HTTP client abstraction for handling API requests.
• pyawx.models: Pydantic models for data validation and serialization.
• pyawx.resources: Resource classes for interacting with AWX resources.
• pyawx.client: Client interface for interacting with the AWX API.

📦 Installation

work in progress

📖 Usage

🔒 Authentication

To interact with the AWX API, you need to authenticate using either Basic Authentication or OAuth2. Here's how to set up both methods:

🔑 Basic Authentication

from pyawxapi.client import Client

# Initialize the client with Basic Authentication
client = Client(
    "https://api.example.com",
    username="your_username",
    password="your_password",
)

# Fetch a job template by name
job_template = client.job_template.fetch("My Job Template")

🔑 OAuth2 Authentication

from pyawxapi.client import Client

# Initialize the client with OAuth2 Authentication
client = Client("https://api.example.com", token="your_oauth2_token")

# Fetch a workflow job template by name
workflow_job_template = client.workflow_job_template.fetch("My Workflow Job Template")

🔄 Working with Resources

The library provides resource-specific classes to interact with different AWX API endpoints. Below are examples of how to work with job templates and workflow job templates.

📜 Job Templates

from pyawxapi.models import JobTemplateModel

# Create a new job template
new_job_template = JobTemplateModel(
    name="My New Job",
    inventory="inventory_1",
    project="project_1",
    playbook="deploy.yml"
)

created_job_template = client.job_template.create(new_job_template)

# Update an existing job template
updated_job_template = JobTemplateModel(
    name="Updated Job Template",
    inventory="inventory_1",
    project="project_1",
    playbook="deploy.yml"
)

client.job_template.update("My Job Template", updated_job_template)

# Delete a job template
client.job_template.delete("My Job Template")

📜 Workflow Job Templates

from pyawxapi.models import WorkflowJobTemplateModel

# Create a new workflow job template
new_workflow = WorkflowJobTemplateModel(
    name="Release Deployment Workflow",
    inventory="prod_inventory",
    extra_vars='{"version": "1.2.3"}'
)
created_workflow = client.workflow_job_template.create(new_workflow)
print(created_workflow)

# Update an existing workflow job template
updated_workflow = WorkflowJobTemplateModel(
    name="Updated Workflow",
    inventory="prod_inventory",
    extra_vars='{"version": "1.2.4"}'
)
client.workflow_job_template.update("Release Deployment Workflow", updated_workflow)

# Delete a workflow job template
client.workflow_job_template.delete("Release Deployment Workflow")

✔️ Data Validation with Pydantic Models

The library uses Pydantic models to ensure that the data conforms to the AWX API's expected structure. This helps in reducing runtime errors by validating the data before sending it to the API.

from pydantic import ValidationError

from pyawxapi.models import JobTemplateModel

# Create a job template with validation
try:
    job_template = JobTemplateModel(
        name="Valid Job Template",
        inventory="inventory_1",
        project="project_1",
        playbook="deploy.yml",
    )
    print("Job template is valid:", job_template)
except ValidationError as e:
    print("Validation error:", e)

🤝 Contributing

work in progress

🧪 Testing

Run unit tests using pytest:

uv run pytest tests

🛠️ Roadmap

work in progress